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Training humans to detect AI-generated faces Edited by Linda B. Smith, Indiana University Bloomington, Bloomington, IN; received January 21, 2026; accepted May 7, 2026 Abstract As AI-generated faces become indistinguishable from real ones, deepfake technology poses escalating threats to information integrity and security.
First impressions made to photographs of faces can depend as much on momentary characteristics of the photographed image (within-person variability) as on consistent properties of the face of the person depicted (between-person variability). Here, we examine two important sources of within-person variability: emotional expression and viewpoint.
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